This copy is for your personal non-commercial use only. To order presentation-ready copies of Toronto Star content for distribution to colleagues, clients or customers, or inquire about permissions/licensing, please go to: www.TorontoStarReprints.com

Amazon puts (shopping) cart before the horse

‘One of Amazon’s big disadvantages is that people have to wait. No one likes waiting.’

First they were trumpeting flying delivery drones.

Now Amazon may be going into the crystal-ball business.

The Seattle-based, e-commerce giant is quietly proposing a system that would send packages on their way to customers before they actually order them.

And unlike its pie-in-the-sky drones idea, Amazon likely has the technology to pursue the prognosticating strategy right now, say experts.

Article Continued Below

“They are already doing it to an extent,” says Murat Kristal, a supply chain and operations management expert at York University’s Schulich School of Business.

Kristal says the same computer and statistical models the company uses to recommend items that a customer “may” want can be taken a step further and allow Amazon to assume that he or she “will” desire them — and that an order is imminent.

In December, the company received a United States Patent for a system that would send out yet-to-be ordered packages from one of its fulfilment centres to distributions hubs close to the anticipated customer.

Called “Anticipatory Package Shipping,” the system would kick that delivery process off before customers place items in their virtual shopping carts.

It would even allow the company to add a full delivery address on a package in transit if the order is placed during shipping.

Unlike its drone idea, which Amazon splashed to the world last year in a 60 Minutes segment, the company is refusing requests to speak about its new shipping scheme.

“Thanks for checking but we have nothing to share on this,” Amazon spokesperson Kelly Cheeseman said in an email to the Star.

But why it might pursue such prognosticating is clear, says Avi Goldfarb, a marketing technology expert at the U of T’s Rotman School of Management.

Goldfarb says that one of the key shortcomings of the e-commerce business is that people don’t like to wait for their purchases.

“Amazon competes with offline stores and one of the nice things about an offline store is when you go and you buy something you actually get to take it home right away,” he says. “And one of Amazon’s big disadvantages is that people have to wait. No one likes waiting.”

Even the company, in its patent filing, acknowledges this gratification delay is a major e-commerce problem: “Electronic commerce using virtual storefronts offers many advantages such as lower cost overhead … and a potential customer base limited only by the reach of the internet,” the document says. “However, one substantial disadvantage to the virtual storefront model is that in many instances, customers cannot receive their merchandise immediately upon purchase.”

These wait times represent the biggest disadvantage Amazon and its online ilk face, Goldfarb says.

“One way to reduce the amount of time people wait is to try and predict what they’re going to buy and make the shipping of that item more efficient,” he says.

The anticipatory delivery system would address this disadvantage by getting goods as close to customers as possible before their order is placed.

“And Amazon absolutely already has technology for trying to guess what people will want,” Goldfarb says, referring to the company’s “people who bought this also bought …” feature.

“What this is saying is they think that tool has become good enough that they can start making their shipping and delivery more efficient because of that.”

Amazon’s current recommendations tool is based largely on the purchasing comparisons it makes between its customers.

“We determine your interests by examining the items you’ve purchased, items you’ve told us you own, items you’ve rated, and item’s you’ve told us you like,” the company says on an internet FAQ page.

“We then compare your activity on our site with that of other customers, and using this comparison, are able to recommend other items that may interest you.”

“Once they have those things near you, you might be able to get a discount on shipping or a discount on something else if you chose that item,” he says. “Or they might have some kind of marketing message on the page that says ‘Well, here’s some items we think you might want and if you order them, by the way, we’ll deliver them tomorrow, or same day.’ ”

But going from recommending to anticipating could prove to be a fraught transition, Kristal and Goldfarb say.

Most obviously, they say, the predictions may be wrong.

“If your algorithms are not good enough then this could be costly,” Goldfarb says. “That’s pitfall No. 1.”

Such imperfect punting would add extra shipping and warehousing costs that would have to be offset, Kristal says, adding that the company would have to decide whether it would be cheaper to ship items back to a main distribution centre or offer them to customers at a discount or even as free promotional gifts.

More from the Toronto Star & Partners

LOADING

Copyright owned or licensed by Toronto Star Newspapers Limited. All rights reserved. Republication or distribution of this content is expressly prohibited without the prior written consent of Toronto Star Newspapers Limited and/or its licensors. To order copies of Toronto Star articles, please go to: www.TorontoStarReprints.com